Triple
T38019485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vishnupad Temple |
E948588
|
entity |
| Predicate | hasSanctumMaterial |
P192192
|
FINISHED |
| Object | black stone |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: black stone | Statement: [Vishnupad Temple, hasSanctumMaterial, black stone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSanctumMaterial Context triple: [Vishnupad Temple, hasSanctumMaterial, black stone]
-
A.
hasSanctumDedicatedTo
Indicates that one entity possesses or contains a sanctum (a sacred or private space) that is dedicated to another entity.
-
B.
hasSpireMaterial
Indicates that the material composition of a spire is a specified substance or material.
-
C.
hasLockGateMaterial
Indicates that a lock gate is made of, or constructed from, a specified material.
-
D.
hasSacredWeapon
Indicates that an entity possesses or is associated with a weapon regarded as holy, consecrated, or religiously significant.
-
E.
hasLanternMaterial
Indicates that an entity’s lantern is made from or composed of a specified material.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76efc10448190aff5fb566b98f952 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcf825ca7081909d06b0df33eb33f9 |
completed | May 7, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fcf42160f0819096812a8bf590875e |
completed | May 7, 2026, 8:20 p.m. |
| PDg | Predicate description generation | batch_69fcf82405c88190a19cecf8e9cc272d |
completed | May 7, 2026, 8:37 p.m. |
Created at: May 3, 2026, 4:20 p.m.